scholarly journals The use of retrotransposons as markers for mapping genes responsible for fitness differences between related Drosophila melanogaster strains

1993 ◽  
Vol 62 (2) ◽  
pp. 125-131 ◽  
Author(s):  
Sergey V. Nuzhdin ◽  
Peter D. Keightley ◽  
Elena G. Pasyukova
Keyword(s):  
Drosophila Melanogaster ◽  
Molecular Markers ◽  
Maximum Likelihood ◽  
Quantitative Trait ◽  
Pericentromeric Region ◽  
Related Strain ◽  
Gene Frequencies ◽  
Ha Gene ◽  
Insertion Sites ◽  
Additional Locus

SummaryHitch-hiking of dispersed mobile elements serving as molecular markers was used as a new tool for mapping quantitative trait loci in Drosophila melanogaster. Two Drosophila strains with high fitness (HA) were backcrossed repeatedly to a closely related strain with low fitness (LA) to initiate experimental populations with expected HA gene frequencies of 1/32. The frequencies of 19 insertion sites of the retrotransposons mdg1 and copia were analyzed after 11 to 17 generations. Frequencies of sites from the HA line increased substantially in the pericentromeric region, indicating that one or more loci responsible for the fitness difference between the strains were located there. A maximum likelihood (ML) procedure was applied to estimate selection coefficients associated with the markers, and this indicated a broad, strongly selected region of the chromosome. At least one additional locus was localized in the middle of the 2L arm. Possible applications of this method are discussed.

scholarly journals On the Differences Between Maximum Likelihood and Regression Interval Mapping in the Analysis of Quantitative Trait Loci

Genetics ◽  
2000 ◽  
Vol 156 (2) ◽  
pp. 855-865 ◽  
Author(s):  
Chen-Hung Kao
Keyword(s):  
Quantitative Trait Loci ◽  
Maximum Likelihood ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Mean Squared Error ◽  
Interval Mapping ◽  
Size Difference ◽  
Ratio Test ◽  
Trait Loci ◽  
Variance Explained

AbstractThe differences between maximum-likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) are investigated analytically and numerically by simulation. The analytical investigation is based on the comparison of the solution sets of the ML and REG methods in the estimation of QTL parameters. Their differences are found to relate to the similarity between the conditional posterior and conditional probabilities of QTL genotypes and depend on several factors, such as the proportion of variance explained by QTL, relative QTL position in an interval, interval size, difference between the sizes of QTL, epistasis, and linkage between QTL. The differences in mean squared error (MSE) of the estimates, likelihood-ratio test (LRT) statistics in testing parameters, and power of QTL detection between the two methods become larger as (1) the proportion of variance explained by QTL becomes higher, (2) the QTL locations are positioned toward the middle of intervals, (3) the QTL are located in wider marker intervals, (4) epistasis between QTL is stronger, (5) the difference between QTL effects becomes larger, and (6) the positions of QTL get closer in QTL mapping. The REG method is biased in the estimation of the proportion of variance explained by QTL, and it may have a serious problem in detecting closely linked QTL when compared to the ML method. In general, the differences between the two methods may be minor, but can be significant when QTL interact or are closely linked. The ML method tends to be more powerful and to give estimates with smaller MSEs and larger LRT statistics. This implies that ML interval mapping can be more accurate, precise, and powerful than REG interval mapping. The REG method is faster in computation, especially when the number of QTL considered in the model is large. Recognizing the factors affecting the differences between REG and ML interval mapping can help an efficient strategy, using both methods in QTL mapping to be outlined.

scholarly journals Respiratory syncytial virus B sequence analysis reveals a novel early genotype

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Juan C. Muñoz-Escalante ◽  
Andreu Comas-García ◽  
Sofía Bernal-Silva ◽  
Daniel E. Noyola
Keyword(s):  
Molecular Markers ◽  
Respiratory Syncytial Virus ◽  
Maximum Likelihood ◽  
Respiratory Infections ◽  
Phylogenetic Analyses ◽  
Detection Methods ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Individual Gene ◽  
Syncytial Virus

AbstractRespiratory syncytial virus (RSV) is a major cause of respiratory infections and is classified in two main groups, RSV-A and RSV-B, with multiple genotypes within each of them. For RSV-B, more than 30 genotypes have been described, without consensus on their definition. The lack of genotype assignation criteria has a direct impact on viral evolution understanding, development of viral detection methods as well as vaccines design. Here we analyzed the totality of complete RSV-B G gene ectodomain sequences published in GenBank until September 2018 (n = 2190) including 478 complete genome sequences using maximum likelihood and Bayesian phylogenetic analyses, as well as intergenotypic and intragenotypic distance matrices, in order to generate a systematic genotype assignation. Individual RSV-B genes were also assessed using maximum likelihood phylogenetic analyses and multiple sequence alignments were used to identify molecular markers associated to specific genotypes. Analyses of the complete G gene ectodomain region, sequences clustering patterns, and the presence of molecular markers of each individual gene indicate that the 37 previously described genotypes can be classified into fifteen distinct genotypes: BA, BA-C, BA-CC, CB1-THB, GB1-GB4, GB6, JAB1-NZB2, SAB1, SAB2, SAB4, URU2 and a novel early circulating genotype characterized in the present study and designated GB0.

scholarly journals Consequences of Recombination Rate Variation on Quantitative Trait Locus Mapping Studies: Simulations Based on the Drosophila melanogaster Genome

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 581-588
Author(s):  
Mohamed A F Noor ◽  
Aimee L Cunningham ◽  
John C Larkin
Keyword(s):  
Quantitative Trait Locus ◽  
Drosophila Melanogaster ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Recombination Rate ◽  
Genome Project ◽  
Gene Density ◽  
Rate Variation ◽  
Trait Locus ◽  
Recombination Rate Variation

Abstract We examine the effect of variation in gene density per centimorgan on quantitative trait locus (QTL) mapping studies using data from the Drosophila melanogaster genome project and documented regional rates of recombination. There is tremendous variation in gene density per centimorgan across this genome, and we observe that this variation can cause systematic biases in QTL mapping studies. Specifically, in our simulated mapping experiments of 50 equal-effect QTL distributed randomly across the physical genome, very strong QTL are consistently detected near the centromeres of the two major autosomes, and few or no QTL are often detected on the X chromosome. This pattern persisted with varying heritability, marker density, QTL effect sizes, and transgressive segregation. Our results are consistent with empirical data collected from QTL mapping studies of this species and its close relatives, and they explain the “small X-effect” that has been documented in genetic studies of sexual isolation in the D. melanogaster group. Because of the biases resulting from recombination rate variation, results of QTL mapping studies should be taken as hypotheses to be tested by additional genetic methods, particularly in species for which detailed genetic and physical genome maps are not available.

scholarly journals Direct determination of retrotransposon transposition rates in Drosophila melanogaster

1994 ◽  
Vol 63 (2) ◽  
pp. 139-144 ◽  
Author(s):  
Sergey V. Nuzhdin ◽  
Trudy F. C. Mackay
Keyword(s):  
Drosophila Melanogaster ◽  
Transposable Element ◽  
Inbred Line ◽  
Copy Number ◽  
Direct Determination ◽  
Hybridization Analysis ◽  
Spontaneous Mutations ◽  
Insertion Sites

SummaryRates of transposition and excision of the Drosophila melanogaster retrotransposon elements mdg3, 297, Doc, roo and copia were estimated directly, by in situ hybridization analysis of their cytological insertion sites in 31 replicates of a highly inbred line that had accumulated spontaneous mutations for approximately 160generations. Estimated transposition rates of Doc, roo and copia were, respectively, 4·2 × 10−5, 3·1 × 10−3 and 1·3 − 10−3; no transpositions of 297 nor mdg3 were observed. Rates of transposition of copia varied significantly among sublines. Excisions were only observed for roo elements, at a rate of 9·0 × 10−6 per element per generation. Copy number averaged over these element families increased 5·9 %; therefore, in these lines the magnitude of the forces opposing transposable element multiplication were weaker than transposition rates.

scholarly journals Behavioral and molecular markers of death in Drosophila melanogaster

2019 ◽  
Vol 126 ◽  
pp. 110707 ◽  
Author(s):  
John Tower ◽  
Siddharth Agrawal ◽  
Muthu Palaniappan Alagappan ◽  
Hans S. Bell ◽  
Marton Demeter ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Molecular Markers

scholarly journals A scenario for the hobo transposable element invasion, deduced from the structure of natural populations of Drosophila melanogaster using tandem TPE repeats

2000 ◽  
Vol 75 (1) ◽  
pp. 13-23 ◽  
Author(s):  
ERIC BONNIVARD ◽  
CLAUDE BAZIN ◽  
BEATRICE DENIS ◽  
DOMINIQUE HIGUET
Keyword(s):  
Drosophila Melanogaster ◽  
Molecular Markers ◽  
World Wide ◽  
Tandem Repeats ◽  
Natural Populations ◽  
The Past ◽  
The World ◽  
Historical Pattern ◽  
The 1960S ◽  
Two Stages

Temporal surveys of hobo transposable elements in natural populations reveal a historical pattern suggesting a recent world-wide invasion of D. melanogaster by these transposons, perhaps following a recent horizontal transfer. To clarify the dynamics of hobo elements in natural populations, and thus to provide further data for our understanding of the hobo invasion, TPE tandem repeats, observed in the polymorphic S region of the element, were used as molecular markers. The number of TPE repeats was studied in 101 current populations from around the world, and in 63 strains collected in the past. This revealed a geographical distribution which seems to have been stable since the beginning of the 1960s. This distribution is compatible with a number of hypotheses for the dynamics of hobo elements. We propose a scenario based on an invasion in two stages: first, a complete invasion by elements with three TPE repeats, followed by the beginning of a new invasion involving hobo elements with five or seven repeats.

scholarly journals Mapping Quantitative Trait Loci for Resistance to Fall Armyworm (Lepidoptera: Noctuidae) Leaf-Feeding Damage in Maize Inbred Mp705

2020 ◽  
Vol 113 (2) ◽  
pp. 956-963 ◽  
Author(s):  
E D Womack ◽  
W P Williams ◽  
J S Smith ◽  
M L Warburton ◽  
D Bhattramakki
Keyword(s):  
Molecular Markers ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Fall Armyworm ◽  
Phenotypic Variance ◽  
Feeding Damage ◽  
Artificial Infestation ◽  
Lepidopteran Insects ◽  
Trait Loci ◽  
Important Pest

Abstract The fall armyworm, Spodoptera frugiperda (J. E. Smith), is an agronomically important pest that severely limits maize (Zea mays (Linnaeus) [Poales: Poaceae]) production. This migrant insect devastates maize plants in many countries threatening the livelihood of millions. Quantitative trait loci (QTL) were mapped to identify chromosomal regions that control resistance to fall armyworm leaf-feeding and to identify molecular markers linked to the target loci for use in marker-assisted selection (MAS). A bi-parental mapping population, comprising 243 F2:3 families from the cross Mp705 (resistant) × Mp719 (susceptible), was evaluated for fall armyworm leaf-feeding damage under artificial infestation over 3 yr. A linkage map comprised of 1,276 single-nucleotide polymorphism and simple sequence repeat molecular markers was constructed. Quantitative trait loci analyses identified two major QTL in bins 4.06 and 9.03 that when combined, explained 35.7% of the phenotypic variance over all environments. Mp705 was responsible for the leaf-feeding damage reducing alleles for both large effect QTL and most of the small effect QTL identified in this study. The QTL identified in bin 9.03 co-locates with a previously identified QTL that controls resistance to leaf-feeding damage in maize by fall armyworm and other lepidopteran insects. The QTL in bin 4.06 is a new source of resistance identified in this study. Beneficial alleles derived from Mp705 for the application of an integrated QTL-MAS approach could accelerate breeding efforts to minimize fall armyworm leaf-feeding in maize.

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